r/cTrader_Club

▲ 6 r/cTrader_Club+1 crossposts

How many shares should you actually buy? A breakdown of five position sizing models

Most of what gets discussed in trading is entries and stops. Almost nobody talks about the third number that actually determines whether a good idea turns into a good trade: how much you buy. You can be early or late on an entry and still come out fine. Size a position wrong and a correct call can still wreck your week.

Here's the thing people skip past: the entry, the stop, and the target can all be identical and you can still end up with wildly different outcomes depending on which sizing method you used to get there. I want to walk through five different ways to answer "how many shares" using the same hypothetical trade, so you can actually see how much the sizing decision alone moves the numbers.

Say you've got a €100,000 account, you're willing to risk 1.2% per trade, and you cap any single position at 40% of the account. You're looking at a stock trading at €205, with a stop at €188 and a target at €236. That's €17 of risk per share and €31 of reward, so the setup itself is about 1:1.8 regardless of how you size it. What changes is everything downstream of that.

**1. Pure risk-based.** You decide the dollar amount you're willing to lose, then divide by the risk per share. 1.2% of €40,000 is €480, divided by €17 risk per share gets you 28 shares. Position value around €5,700, max loss capped at €476. This is the most disciplined version, the loss is the same dollar amount no matter what you're trading, but it can leave you holding tiny positions on wide-stop setups.

**2. Conviction-adjusted.** Same starting point as pure risk-based, but scaled down when your own signals don't agree with each other. If your indicators are mixed rather than unanimous, you size smaller on the same setup. In this example that knocks 28 shares down to 24, a modest haircut. The logic is sound, you're less sure, so you risk less, but it only works if you're honest about how you're defining "sure" in the first place, otherwise it's just vibes with a formula wrapped around them.

**3. Exposure-based.** Forget the stop entirely, just allocate a fixed percentage of the account to the position. 10% of €100,000 divided by the €205 entry price gets you 48 shares. Same stop as before means your actual dollar risk went up to €816, even though you "only" used 10% of the account. This is the trap with exposure-based sizing, it feels conservative because the percentage is small, but it completely ignores stop distance, so a wide stop quietly produces more risk than a tight one at the identical allocation.

**4. EV-scaled.** Take the exposure-based number and multiply it by how strong you think the setup is. A "strong" conviction multiplier of 1.5x on 48 shares gets you to 72 shares, nearly triple the pure risk-based size, with max loss now over €1,200. This can work, but only if "strong" means something consistent and repeatable, not just how confident you feel that morning.

**5. Aggressive.** Go all the way to your max per-symbol allocation. 40% of the account on a €205 stock is 195 shares, max loss over €3,300, nearly seven times the pure risk-based version on the exact same trade. There's a place for this, a genuinely rare, high-conviction setup where you've decided in advance you're willing to take the drawdown, but it should be a deliberate, bounded exception you set rules around ahead of time, not your default.

Lay all five side by side and the spread is the whole point: same entry, same stop, same target, and your share count moves from 28 to 195 depending purely on which model you picked. Screenshot below is this exact trade run through five models at once, same numbers as above:

A few patterns worth avoiding regardless of which model you use: sizing on emotion after a win or a loss, sizing purely on how confident you feel while skipping the actual risk math, ignoring how far your stop is from entry, using one fixed size for every trade regardless of setup, or going so small that fees and slippage eat a meaningful chunk of whatever edge you had. None of these are sizing "methods," they're just the absence of one.

The question worth asking before every trade isn't "is this a good stock." It's "how much am I actually buying if I turn out to be wrong." Pick a model, know exactly why you picked it, and apply it the same way every time. That consistency is most of what separates sizing as a discipline from sizing as a guess with extra steps.

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u/three_red_candles — 8 days ago
▲ 6 r/cTrader_Club+2 crossposts

How do you actually build an intraday view when price can go either way?

Trying to understand how experienced traders form an intraday view. 6. Being most important.

If the S&P 500 is at 6,500, nothing says it has to hit 6,600 or 6,400. Same with EUR/USD or BTC. So how do you get from "could go anywhere" to an actual trade?

  1. Do you start the day with a bias, or stay neutral and let price show you something first?

  2. How much does the open matter? When there's a gap, how do you judge whether it fills or runs? Do you wait out the first 15 to 30 minutes?

  3. What tells you there's enough evidence to go long or short? And what tells you "this isn't working, I'm out"?

  4. Stop hunts are where I get lost. Price takes out an obvious low, triggers stops, then rips. How do you tell that apart from a real breakdown? Wider SL, waiting for a candle close, something else?

  5. Do you set the view on the Daily or 4H and use lower timeframes only for entry? Or can an intraday setup flip your bigger picture?

**6. How do you read new highs? Say BTC rallies to a fresh high at 84,500 and pulls back to 84,000. Is that a dip to buy or the start of a reversal to short? What would you need to see before picking a side?**

Would love to hear how this actually works in your head, especially from people who've been at it for a while and profiting.

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u/ParfaitSpirited5116 — 10 days ago
▲ 172 r/cTrader_Club+1 crossposts

Zero quant background, built an NQ futures bot with Claude. It passes 4 of my robustness tests and is shaky on 2. Roast my method.

No quant background. I built an automated NQ futures bot over the last few months with Claude (Anthropic's AI) doing the coding and testing, and I'd like people who've done this to pick the method apart before I put money on it.

**Quick version (details in the images):**
- 9-year walk-forward, 2,437 trades, every trade out-of-sample, fixed 1 micro, costs charged
- Profit factor 1.24 (1.19 with costs doubled), +$25k at 1 micro, worst drawdown $3.5k
- Passes: doubled costs, 10,000-run block bootstrap, a 1,000-shuffle luck test on its long/short calls
- Shaky: deflated Sharpe once all 557 variants I tried are counted, and most of the profit is 2021+
- 13+ other ideas tested and failed, all shown

**Goal:** pass a Topstep 50K ($2k trailing drawdown). The edge isn't the problem; the drawdown is.

**What I'd love opinions on:**

  1. Most profit is 2021 onward. Regime dependence or a model that improved with more data? How would you tell?
  2. With a $2k trailing limit, how would you size this, or is a prop firm the wrong home for it?
  3. What's the first thing you'd check for look-ahead bias?

Also looking for a few people or a community to talk this through with. Feels like I am working on something that nobody understands. Strategy details stay private, but I'll answer anything about the testing. Not selling anything. Backtest, not financial advice.

u/Historical_List_9657 — 14 days ago